Angiostrongylus cantonensis DNA in cerebrospinal fluid of persons with eosinophilic meningitis, Laos

Definitive identification of Angiostrongylus cantonensis parasites from clinical specimens is difficult. As a result, regional epidemiology and burden are poorly characterized. To ascertain presence of this parasite in patients in Laos with eosinophilic meningitis, we performed quantitative PCRs on 36 cerebrospinal fluid samples; 4 positive samples confirmed the parasite's presence

Pre-cut filter paper for detecting anti-Japanese encephalitis virus IgM from dried cerebrospinal fluid spots

Background The use of filter paper as a simple, inexpensive tool for storage and transportation of blood, 'Dried Blood Spots' or Guthrie cards, for diagnostic assays is well-established. In contrast, there are a paucity of diagnostic evaluations of dried cerebrospinal fluid (CSF) spots. These have potential applications in low-resource settings, such as Laos, where laboratory facilities for central nervous system (CNS) diagnostics are only available in Vientiane. In Laos, a major cause of CNS infection is Japanese encephalitis virus (JEV). We aimed to develop a dried CSF spot protocol and to evaluate its diagnostic performance using the World Health Organisation recommended anti-JEV IgM antibody capture enzyme-linked immunosorbent assay (JEV MAC-ELISA). Methodology and Principal Findings Sample volumes, spotting techniques and filter paper type were evaluated using a CSF-substitute of anti-JEV IgM positive serum diluted in Phosphate Buffer Solution (PBS) to end-limits of detection by JEV MAC-ELISA. A conventional protocol, involving eluting one paper punch in 200 mu l PBS, did not detect the end-dilution, nor did multiple punches utilising diverse spotting techniques. However, pre-cut filter paper enabled saturation with five times the volume of CSF-substitute, sufficiently improving sensitivity to detect the end-dilution. The diagnostic accuracy of this optimised protocol was compared with routine, neat CSF in a pilot, retrospective study of JEV MAC-ELISA on consecutive CSF samples, collected 2009-15, from three Lao hospitals. In comparison to neat CSF, 132 CSF samples stored as dried CSF spots for one month at 25-30 degrees C showed 81.6%(65.7-92.3 95%CI) positive agreement, 96.8% (91.0-99.3 95% CI) negative agreement, with a kappa coefficient of 0.81 (0.70-0.92 95% CI). Conclusions/Significance The novel design of pre-cut filter paper saturated with CSF could provide a useful tool for JEV diagnostics in settings with limited laboratory access. It has the potential to improve national JEV surveillance and inform vaccination policies. The saturation of filter paper has potential use in the wider context of pathogen detection, including dried spots for detecting other analytes in CSF, and other body fluids

On two-dimensional Bessel functions

The general properties of two-dimensional generalized Bessel functions are discussed. Various asymptotic approximations are derived and applied to analyze the basic structure of the two-dimensional Bessel functions as well as their nodal lines.Comment: 25 pages, 17 figure

Development of a short form of Mini-Mental State Examination for the screening of dementia in older adults with a memory complaint: a case control study

<p>Abstract</p> <p>Background</p> <p>Primary care physicians need a brief and accurate screening test of dementia. The objective of this study was to determine whether a short form of Mini-Mental State Examination (SMMSE) was as accurate as the Mini-Mental State Examination (MMSE) in screening dementia.</p> <p>Methods</p> <p>Based on case control design study, SMMSE and MMSE were assessed in 184 community-dwelling older adults (mean age 81.3 ± 6.5 years, 71.7% women) with memory complaint sent by their primary care physician to a memory clinic. Included participants were separated into two groups: cognitively healthy individuals and demented individuals.</p> <p>Results</p> <p>The trade-off between sensitivity and specificity of the SMMSE for clinically diagnosed dementia was 4. Based on the cut-off value ≤ 4 for SMMSE and a cut-off value ≤ 24 for MMSE, the sensitivity of both tests was similar (89.5% for SMMSE versus 90.0% for MMSE), whereas the specificity, the positive predictive values (PPV) and the negative predictive values (NPV) were higher for SMMSE compared to MMSE (85.4 versus 75.5% for specificity; 95.5% versus 92.8% for PPV; 70.0 versus 68.9 for NPV). The positive and negative Likehood Ratio (LR) of SMMSE were higher than those of MMSE (respectively, 6.1 versus 3.7; 8.1 versus 7.7). In addition, odds ratio (OR) for dementia was higher for the SMMSE compared to the MMSE (OR = 49.8 with 95% confident interval (CI) [18.0; 137.8] versus OR = 28.6 with 95% CI [11.6; 70.3]).</p> <p>Conclusions</p> <p>SMMSE seems to be an efficient short screening test for dementia among community-dwelling older adults with a memory complaint. Further research is needed to confirm its predictive values among unselected primary care older patients.</p

Repurposing rapid diagnostic tests to detect falsified vaccines in supply chains

Substandard (including degraded) and falsified (SF) vaccines are a relatively neglected issue with serious global implications for public health. This has been highlighted during the rapid and widespread rollout of COVID-19 vaccines. There has been increasing interest in devices to screen for SF non-vaccine medicines including tablets and capsules to empower inspectors and standardise surveillance. However, there has been very limited published research focussed on repurposing or developing new devices for screening for SF vaccines. To our knowledge, rapid diagnostic tests (RDTs) have not been used for this purpose but have important potential for detecting falsified vaccines. We performed a proof-in-principle study to investigate their diagnostic accuracy using a diverse range of RDT-vaccine/falsified vaccine surrogate pairs. In an initial assessment, we demonstrated the utility of four RDTs in detecting seven vaccines. Subsequently, the four RDTs were evaluated by three blinded assessors with seven vaccines and four falsified vaccines surrogates. The results provide preliminary data that RDTs could be used by multiple international organisations, national medicines regulators and vaccine manufacturers/distributors to screen for falsified vaccines in supply chains, aligned with the WHO global ‘Prevent, Detect and Respond’ strategy

Structural Phase Transitions and Sodium Ordering in Na0.5CoO2: a Combined Electron Diffraction and Raman Spectroscopy Study

The nonstoichiometric NaxCoO2 system exhibits extraordinary physical properties that correlate with temperature and Na concentration in its layered lattice without evident long-range structure modification when conventional crystallographic techniques are applied. For instance, Na0.7CoO2, a thermodynamically stable phase, shows large thermoelectric power; water-intercalated Na0.33CoO2.1.3H2O is a newly discovered superconductor with Tc ~ 4K, and Na0.5CoO2 exhibits an unexpected charge ordering transition at around Tco ~ 55 K. Recent studies suggest that the transport and magnetic properties in the NaxCoO2 system strongly depend on the charge carrier density and local structural properties. Here we report a combined variable temperature transmission electron microscopy and Raman scattering investigation on structural transformations in Na0.5CoO2 single crystals. A series of structural phase transitions in the temperature range from 80 K to 1000 K are directly identified and the observed superstructures and modulated phases can be interpreted by Na-ordering. The Raman scattering measurements reveal phase separation and a systematic evolution of active modes along with phase transitions. Our work demonstrates that the high mobility and ordering of sodium cations among the CoO2 layers are a key factor for the presence of complex structural properties in NaxCoO2 materials, and also demonstrate that the combination of electron diffraction and Raman spectroscopy measurements is an efficient way for studying the cation ordering and phase transitions in related systems.Comment: 22 pages, 5 figure

Three main stressors acting on the Ria Formosa lagoonal system (Southern Portugal): physical stress, organic matter pollution and the land–ocean gradient

During the last 15 years of the 20th century, several researchers carried out extensive sampling of benthic macrofauna communities in the Ria Formosa lagoon. The main objective of this paper is to discern the main communities of benthic fauna of the Ria Formosa and the leading stressors that limit them based on this large data set. The high species richness and high diversity values observed at most of the stations or groups of stations indicate a good ecological status, with the exception of the sewage-impacted areas and the physically stressed areas. It was possible to define three main stressors acting on the Ria Formosa. The most important is the physical stress imposed by the limited water renewal in some areas of the Ria Formosa. The second is the nutrient and organic matter pollution that is limited to the vicinity of the sewage outfall stations and to some locations of the Ria Formosa. This is due to the dual effects of the low residence time of water, but also due to a degradation of water quality in places of relatively restricted water circulation but with high primary production, symptoms of eutrophication. The third stressor is the natural land-ocean gradient, denoting the influence of seawater exchanges and emersion time, attenuated by the high water exchange rates of Ria Formosa. It was possible to differentiate the anthropogenic stress from the natural physical stress through the application of multivariate analysis. However, both structural (species richness and diversity indices) and functional indicators (trophic composition) indicate the same trend - low species richness, low diversity indices, and a community dominated by detritivores species at the locations characterized by high anthropogenic impact or by physical stress. The physically stressed areas were dominated by chironomid larvae and hydrobiid gastropods and the most polluted areas were dominated by oligochaetes, mainly tubificids

A new method for 2D gel spot alignment: application to the analysis of large sample sets in clinical proteomics

<p>Abstract</p> <p>Background</p> <p>In current comparative proteomics studies, the large number of images generated by 2D gels is currently compared using spot matching algorithms. Unfortunately, differences in gel migration and sample variability make efficient spot alignment very difficult to obtain, and, as consequence most of the software alignments return noisy gel matching which needs to be manually adjusted by the user.</p> <p>Results</p> <p>We present Sili2DGel an algorithm for automatic spot alignment that uses data from recursive gel matching and returns meaningful Spot Alignment Positions (SAP) for a given set of gels. In the algorithm, the data are represented by a graph and SAP by specific subgraphs. The results are returned under various forms (clickable synthetic gel, text file, etc.). We have applied Sili2DGel to study the variability of the urinary proteome from 20 healthy subjects.</p> <p>Conclusion</p> <p>Sili2DGel performs noiseless automatic spot alignment for variability studies (as well as classical differential expression studies) of biological samples. It is very useful for typical clinical proteomic studies with large number of experiments.</p

An elitist quantum-inspired evolutionary algorithm for the flexible job-shop scheduling problem

The flexible job shop scheduling problem (FJSP) is vital to manufacturers especially in today’s constantly changing environment. It is a strongly NP-hard problem and therefore metaheuristics or heuristics are usually pursued to solve it. Most of the existing metaheuristics and heuristics, however, have low efficiency in convergence speed. To overcome this drawback, this paper develops an elitist quantum-inspired evolutionary algorithm. The algorithm aims to minimise the maximum completion time (makespan). It performs a global search with the quantum-inspired evolutionary algorithm and a local search with a method that is inspired by the motion mechanism of the electrons around an atomic nucleus. Three novel algorithms are proposed and their effect on the whole search is discussed. The elitist strategy is adopted to prevent the optimal solution from being destroyed during the evolutionary process. The results show that the proposed algorithm outperforms the best-known algorithms for FJSPs on most of the FJSP benchmarks

Modularization of biochemical networks based on classification of Petri net t-invariants

<p>Abstract</p> <p>Background</p> <p>Structural analysis of biochemical networks is a growing field in bioinformatics and systems biology. The availability of an increasing amount of biological data from molecular biological networks promises a deeper understanding but confronts researchers with the problem of combinatorial explosion. The amount of qualitative network data is growing much faster than the amount of quantitative data, such as enzyme kinetics. In many cases it is even impossible to measure quantitative data because of limitations of experimental methods, or for ethical reasons. Thus, a huge amount of qualitative data, such as interaction data, is available, but it was not sufficiently used for modeling purposes, until now. New approaches have been developed, but the complexity of data often limits the application of many of the methods. Biochemical Petri nets make it possible to explore static and dynamic qualitative system properties. One Petri net approach is model validation based on the computation of the system's invariant properties, focusing on t-invariants. T-invariants correspond to subnetworks, which describe the basic system behavior.</p> <p>With increasing system complexity, the basic behavior can only be expressed by a huge number of t-invariants. According to our validation criteria for biochemical Petri nets, the necessary verification of the biological meaning, by interpreting each subnetwork (t-invariant) manually, is not possible anymore. Thus, an automated, biologically meaningful classification would be helpful in analyzing t-invariants, and supporting the understanding of the basic behavior of the considered biological system.</p> <p>Methods</p> <p>Here, we introduce a new approach to automatically classify t-invariants to cope with network complexity. We apply clustering techniques such as UPGMA, Complete Linkage, Single Linkage, and Neighbor Joining in combination with different distance measures to get biologically meaningful clusters (t-clusters), which can be interpreted as modules. To find the optimal number of t-clusters to consider for interpretation, the cluster validity measure, Silhouette Width, is applied.</p> <p>Results</p> <p>We considered two different case studies as examples: a small signal transduction pathway (pheromone response pathway in <it>Saccharomyces cerevisiae</it>) and a medium-sized gene regulatory network (gene regulation of Duchenne muscular dystrophy). We automatically classified the t-invariants into functionally distinct t-clusters, which could be interpreted biologically as functional modules in the network. We found differences in the suitability of the various distance measures as well as the clustering methods. In terms of a biologically meaningful classification of t-invariants, the best results are obtained using the Tanimoto distance measure. Considering clustering methods, the obtained results suggest that UPGMA and Complete Linkage are suitable for clustering t-invariants with respect to the biological interpretability.</p> <p>Conclusion</p> <p>We propose a new approach for the biological classification of Petri net t-invariants based on cluster analysis. Due to the biologically meaningful data reduction and structuring of network processes, large sets of t-invariants can be evaluated, allowing for model validation of qualitative biochemical Petri nets. This approach can also be applied to elementary mode analysis.</p